scholarly journals Axonal pathology in hPSC-based models of Parkinson’s disease results from loss of Nrf2 transcriptional activity at the Map1b gene locus

2019 ◽  
Vol 116 (28) ◽  
pp. 14280-14289 ◽  
Author(s):  
Christopher Czaniecki ◽  
Tammy Ryan ◽  
Morgan G. Stykel ◽  
Jennifer Drolet ◽  
Juliane Heide ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Differentially Expressed Gene ◽  
Antioxidant Response ◽  
Differentially Expressed ◽  
Axonal Pathology ◽  
Gene Enhancer ◽  
Antioxidant Response Elements ◽  
Gene Ontologies

While mutations in theSNCAgene (α-synuclein [α-syn]) are causal in rare familial forms of Parkinson’s disease (PD), the prevalence of α-syn aggregates in the cortices of sporadic disease cases emphasizes the need to understand the link between α-syn accumulation and disease pathogenesis. By employing a combination of human pluripotent stem cells (hPSCs) that harbor theSNCA-A53T mutation contrasted against isogenic controls, we evaluated the consequences of α-syn accumulation in human A9-type dopaminergic (DA) neurons (hNs). We show that the early accumulation of α-syn inSNCA-A53T hNs results in changes in gene expression consistent with the expression profile of the substantia nigra (SN) from PD patients, analyzed post mortem. Differentially expressed genes from both PD patient SN andSNCA-A53T hNs were associated with regulatory motifs transcriptionally activated by the antioxidant response pathway, particularly Nrf2 gene targets. Differentially expressed gene targets were also enriched for gene ontologies related to microtubule binding processes. We thus assessed the relationship between Nrf2-mediated gene expression and neuritic pathology inSNCA-A53T hNs. We show thatSNCA-mutant hNs have deficits in neuritic length and complexity relative to isogenic controls as well as contorted axons with Tau-positive varicosities. Furthermore, we show that mutant α-syn fails to complex with protein kinase C (PKC), which, in turn, results in impaired activation of Nrf2. These neuritic defects result from impaired Nrf2 activity on antioxidant response elements (AREs) localized to a microtubule-associated protein (Map1b) gene enhancer and are rescued by forced expression of Map1b as well as by both Nrf2 overexpression and pharmaceutical activation in PD neurons.

scholarly journals Transcriptomic profiles in Parkinson’s disease

2020 ◽  
pp. 153537022096732
Author(s):  
Lille Kurvits ◽  
Freddy Lättekivi ◽  
Ene Reimann ◽  
Liis Kadastik-Eerme ◽  
Kristjan M Kasterpalu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Substantia Nigra ◽  
Brain Tissue ◽  
Differentially Expressed Genes ◽  
Meta Analysis ◽  
Rank Aggregation ◽  
Differentially Expressed ◽  
Peripheral Tissues

Transcriptomics in Parkinson’s disease offers insights into the pathogenesis of Parkinson’s disease but obtaining brain tissue has limitations. In order to bypass this issue, we profile and compare differentially expressed genes and enriched pathways (KEGG) in two peripheral tissues (blood and skin) of 12 Parkinson’s disease patients and 12 healthy controls using RNA-sequencing technique and validation with RT-qPCR. Furthermore, we compare our results to previous Parkinson’s disease post mortem brain tissue and blood results using the robust rank aggregation method. The results show no overlapping differentially expressed genes or enriched pathways in blood vs. skin in our sample sets (25 vs. 1068 differentially expressed genes with an FDR ≤ 0.05; 1 vs. 9 pathways in blood and skin, respectively). A meta-analysis from previous transcriptomic sample sets using either microarrays or RNA-Seq yields a robust rank aggregation list of cortical gene expression changes with 43 differentially expressed genes; a list of substantia nigra changes with 2 differentially expressed genes and a list of blood changes with 1 differentially expressed gene being statistically significant at FDR ≤ 0.05. In cortex 1, KEGG pathway was enriched, four in substantia nigra and two in blood. None of the differentially expressed genes or pathways overlap between these tissues. When comparing our previously published skin transcription analysis, two differentially expressed genes between the cortex robust rank aggregation and skin overlap. In this study, for the first time a meta-analysis is applied on transcriptomic sample sets in Parkinson’s disease. Simultaneously, it explores the notion that Parkinson’s disease is not just a neuronal tissue disease by exploring peripheral tissues. The comparison of different Parkinson’s disease tissues yields surprisingly few significant differentially expressed genes and pathways, suggesting that divergent gene expression profiles in distinct cell lineages, metabolic and possibly iatrogenic effects create too much transcriptomic noise for detecting significant signal. On the other hand, there are signs that point towards Parkinson’s disease-specific changes in non-neuronal peripheral tissues in Parkinson’s disease, indicating that Parkinson’s disease might be a multisystem disorder.

scholarly journals The Interaction of lncRNA XLOC-2222497, AKR1C1, and Progesterone in Porcine Endometrium and Pregnancy

2020 ◽  
Vol 21 (9) ◽  
pp. 3232
Author(s):  
Tao Su ◽  
Haile Yu ◽  
Gan Luo ◽  
Mengxia Wang ◽  
Changfan Zhou ◽  
...  
Keyword(s):  
Cellular Localization ◽  
Core Promoter ◽  
Differentially Expressed Gene ◽  
Antioxidant Response ◽  
Differentially Expressed ◽  
Related Factor ◽  
Luciferase Activity Assay ◽  
Antioxidant Response Elements ◽  
Yorkshire Pigs ◽  
The Difference

The endometrium is an important tissue for pregnancy and plays an important role in reproduction. In this study, high-throughput transcriptome sequencing was performed in endometrium samples of Meishan and Yorkshire pigs on days 18 and 32 of pregnancy. Aldo-keto reductase family 1 member C1 (AKR1C1) was found to be a differentially expressed gene, and was identified by quantitative real-time PCR (qRT-PCR) and Western blot. Immunohistochemistry results revealed the cellular localization of the AKR1C1 protein in the endometrium. Luciferase activity assay demonstrated that the AKR1C1 core promoter region was located in the region from −706 to −564, containing two nuclear factor erythroid 2-related factor 2 (NRF2) binding sites (antioxidant response elements, AREs). XLOC-2222497 was identified as a nuclear long non-coding RNA (lncRNA) highly expressed in the endometrium. XLOC-2222497 overexpression and knockdown have an effect on the expression of AKR1C1. Endocrinologic measurement showed the difference in progesterone levels between Meishan and Yorkshire pigs. Progesterone treatment upregulated AKR1C1 and XLOC-2222497 expression in porcine endometrial epithelial cells. In conclusion, transcriptome analysis revealed differentially expressed transcripts during the early pregnancy process. Further experiments demonstrated the interaction of XLOC-2222497/AKR1C1/progesterone in the endometrium and provided new potential targets for pregnancy maintenance and its control.

scholarly journals Disease Duration Influences Gene Expression in Neuromelanin-Positive Cells From Parkinson’s Disease Patients

2021 ◽  
Vol 14 ◽  
Author(s):  
Katarína Tiklová ◽  
Linda Gillberg ◽  
Nikolaos Volakakis ◽  
Hilda Lundén-Miguel ◽  
Lina Dahl ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Substantia Nigra ◽  
Lewy Body Disease ◽  
Dopamine Neurons ◽  
Differentially Expressed ◽  
Incidental Lewy Body Disease ◽  
Advanced Stages ◽  
Midbrain Dopamine

Analyses of gene expression in cells affected by neurodegenerative disease can provide important insights into disease mechanisms and relevant stress response pathways. Major symptoms in Parkinson’s disease (PD) are caused by the degeneration of midbrain dopamine (mDA) neurons within the substantia nigra. Here we isolated neuromelanin-positive dopamine neurons by laser capture microdissection from post-mortem human substantia nigra samples recovered at both early and advanced stages of PD. Neuromelanin-positive cells were also isolated from individuals with incidental Lewy body disease (ILBD) and from aged-matched controls. Isolated mDA neurons were subjected to genome-wide gene expression analysis by mRNA sequencing. The analysis identified hundreds of dysregulated genes in PD. Results showed that mostly non-overlapping genes were differentially expressed in ILBD, subjects who were early after diagnosis (less than five years) and those autopsied at more advanced stages of disease (over five years since diagnosis). The identity of differentially expressed genes suggested that more resilient, stably surviving DA neurons were enriched in samples from advanced stages of disease, either as a consequence of positive selection of a less vulnerable long-term surviving mDA neuron subtype or due to up-regulation of neuroprotective gene products.

Differentially expressed gene profile in the 6-hydroxy-dopamine-induced cell culture model of Parkinson's disease

2012 ◽  
Vol 507 (1) ◽  
pp. 10-15 ◽  
Author(s):  
Carmen Noelker ◽  
Michael Schwake ◽  
Monika Balzer-Geldsetzer ◽  
Michael Bacher ◽  
Julius Popp ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Cell Culture ◽  
Parkinson's Disease ◽  
Differentially Expressed Gene ◽  
Differentially Expressed ◽  
Cell Culture Model ◽  
Gene Profile ◽  
Culture Model

Decoding Psoriasis: Integrated Bioinformatics Approach to Understand Hub Genes and Involved Pathways

2020 ◽  
Vol 26 (29) ◽  
pp. 3619-3630
Author(s):  
Saumya Choudhary ◽  
Dibyabhaba Pradhan ◽  
Noor S. Khan ◽  
Harpreet Singh ◽  
George Thomas ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Gene ◽  
Therapeutic Targets ◽  
Interaction Network ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Keratinocyte Differentiation ◽  
Hub Genes ◽  
Lesional Skin ◽  
Ncbi Gene Expression Omnibus

Background: Psoriasis is a chronic immune mediated skin disorder with global prevalence of 0.2- 11.4%. Despite rare mortality, the severity of the disease could be understood by the accompanying comorbidities, that has even led to psychological problems among several patients. The cause and the disease mechanism still remain elusive. Objective: To identify potential therapeutic targets and affecting pathways for better insight of the disease pathogenesis. Method: The gene expression profile GSE13355 and GSE14905 were retrieved from NCBI, Gene Expression Omnibus database. The GEO profiles were integrated and the DEGs of lesional and non-lesional psoriasis skin were identified using the affy package in R software. The Kyoto Encyclopaedia of Genes and Genomes pathways of the DEGs were analyzed using clusterProfiler. Cytoscape, V3.7.1 was utilized to construct protein interaction network and analyze the interactome map of candidate proteins encoded in DEGs. Functionally relevant clusters were detected through Cytohubba and MCODE. Results: A total of 1013 genes were differentially expressed in lesional skin of which 557 were upregulated and 456 were downregulated. Seven dysregulated genes were extracted in non-lesional skin. The disease gene network of these DEGs revealed 75 newly identified differentially expressed gene that might have a role in development and progression of the disease. GO analysis revealed keratinocyte differentiation and positive regulation of cytokine production to be the most enriched biological process and molecular function. Cytokines -cytokine receptor was the most enriched pathways. Among 1013 identified DEGs in lesional group, 36 DEGs were found to have altered genetic signature including IL1B and STAT3 which are also reported as hub genes. CCNB1, CCNA2, CDK1, IL1B, CXCL8, MKI 67, ESR1, UBE2C, STAT1 and STAT3 were top 10 hub gene. Conclusion: The hub genes, genomic altered DEGs and other newly identified differentially dysregulated genes would improve our understanding of psoriasis pathogenesis, moreover, the hub genes could be explored as potential therapeutic targets for psoriasis.

Gene Set Correlation Analysis and Visualization Using Gene Expression Data

2020 ◽  
Vol 15 ◽  
Author(s):  
Chen-An Tsai ◽  
James J. Chen
Keyword(s):  
Gene Expression ◽  
Correlation Analysis ◽  
Gene Expression Data ◽  
Differentially Expressed Gene ◽  
Differentially Expressed ◽  
Superior Performance ◽  
Expression Data ◽  
Gene Set ◽  
Gene Sets ◽  
Set Correlation

Background: Gene set enrichment analyses (GSEA) provide a useful and powerful approach to identify differentially expressed gene sets with prior biological knowledge. Several GSEA algorithms have been proposed to perform enrichment analyses on groups of genes. However, many of these algorithms have focused on identification of differentially expressed gene sets in a given phenotype. Objective: In this paper, we propose a gene set analytic framework, Gene Set Correlation Analysis (GSCoA), that simultaneously measures within and between gene sets variation to identify sets of genes enriched for differential expression and highly co-related pathways. Methods: We apply co-inertia analysis to the comparisons of cross-gene sets in gene expression data to measure the costructure of expression profiles in pairs of gene sets. Co-inertia analysis (CIA) is one multivariate method to identify trends or co-relationships in multiple datasets, which contain the same samples. The objective of CIA is to seek ordinations (dimension reduction diagrams) of two gene sets such that the square covariance between the projections of the gene sets on successive axes is maximized. Simulation studies illustrate that CIA offers superior performance in identifying corelationships between gene sets in all simulation settings when compared to correlation-based gene set methods. Result and Conclusion: We also combine between-gene set CIA and GSEA to discover the relationships between gene sets significantly associated with phenotypes. In addition, we provide a graphical technique for visualizing and simultaneously exploring the associations of between and within gene sets and their interaction and network. We then demonstrate integration of within and between gene sets variation using CIA and GSEA, applied to the p53 gene expression data using the c2 curated gene sets. Ultimately, the GSCoA approach provides an attractive tool for identification and visualization of novel associations between pairs of gene sets by integrating co-relationships between gene sets into gene set analysis.

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